Li Nan [1]} explored the distribution characteristics and sentiment transformation regularities of emojis in microblog comments from multiple perspectives. The paper classified emojis into high sentiment stability and low sentiment stability based on thresholds and experiment confirmed that emojis can be used in opinion analysis to achieve more accurate sentiment classification. Novak P [2]} constructed a sentiment lexicon containing 751 emojis, and experiments demonstrated that comments with emoji expressed more positive sentiments than those without emoji. Pohl [3]} investigated the similarity problem of emoji in terms of emoji keywords and emoji embeddings.Experiments verified the model's effectiveness in capturing associations between each emoji. Ben Eisner [4]}trained emoji and corresponding descriptive textual information to propose an emoji2vec model for emoji pre-trained embeddings.
